Upcoming third generation wireless systems are intended to have the ability to transmit high speed data, video and multimedia traffic, as well as voice signals to mobile users. Careful choices of modulation, coding, power control and detection methods need to be made in order to make good use of the available channels.
The power of a wireless signal received by a terminal device (e.g. mobile phone) is susceptible to constructive and destructive interference occurring as the device moves relative to signal scattering objects such as buildings. Fluctuations in the signal strength occur due to Doppler effects as the mobile device moves. Devices which themselves are not moving may still be susceptible to constructive and destructive interference occurring as other objects in the environment around them move their relative positions.
The power of the received wireless signal is given by the squared modulus of the complex phasor corresponding to the amplitude and phase of the received signal. Adaptive modulation may be used to provide a modulation technique appropriate to the instantaneous power level of the received signal. If the received signal is strong (i.e. is of high power), then Quadrature Amplitude Modulation (QAM) can be used, which maximises the data transmission rate. Alternatively, if the received signal is weak (i.e. is of lower power), then Quadrature Phase Shift Keying (QPSK) is more appropriate.
The mobile device is able to measure the power of the received signal at any given time. However, there is an inherent delay (e.g. 2 to 10 ms) in transmitting this information from the mobile device back to the transmitter and then processing the information. There is insufficient time to enable the transmitter to receive and process this information before making the decision as to which modulation technique to employ. This is because the power of the received signal fluctuates because of the Doppler effects, and so, within an increment of time, any measured signal strength will no longer be current. Thus, in order to be able to select the most appropriate modulation technique, it is necessary to be able to predict what the received signal power will be at an increment of time in the future.
Some prior approaches to the problem of Modulation and Coding Scheme Prediction (MCSP) are reviewed by A. Duel-Hallen, S. Hu and H. Hallen in “Long-Range Prediction of Fading Signals—Enabling Adapting Transmission for Mobile Radio Channels” (IEEE Signal Processing Magazine, May 2000).
These prior approaches are based on the concept of predicting future values of the complex channel, rather than future values of the real channel power (i.e. magnitude squared of the complex channel value). These alternative techniques use, as their input, noisy measured historical complex channel values, rather than measured real channel power values. Such techniques described by Duel-Hallen et al., and elsewhere, include Linear Prediction techniques (e.g. the Wiener filter) and Non-Linear techniques. Typical examples of Non-Linear Prediction techniques are the Fourier Predictor and Capon's Predictor. The Non-Linear complex channel prediction techniques attempt to model the channel as a set of discrete sources with given Doppler frequency, phase and complex amplitude, and use this information to predict future complex channel values. Whilst such Linear and Non-Linear techniques may in some cases offer acceptable performance, they have the following disadvantages:                They require the use of known training symbols, which leads to a transmission overhead        They require a long observation interval in order to extract enough information to accurately characterise the complex fading process        They tend to be computationally complex        Their complexity increases significantly for Multiple-Input-Multiple-Output (MIMO) and dispersive channels, since each path must be tracked separately.        